import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal

# # 均值向量
# mean = np.array([5176.39782807, 2998.34589978])
# print(mean)
# # 协方差矩阵
# cov = np.array([[1, 0], [0, 1]])

# # 生成二维高斯分布
# x, y = np.mgrid[5176.39782807-3:5176.39782807+3:.01, 2998.34589978-3:2998.345899783:.01]
# pos = np.dstack((x, y))
# rv = multivariate_normal(mean, cov)
# z = rv.pdf(pos)
# # print(x)
# # print(pos)
# print(z)
# # 绘制等高线图
# fig = plt.figure()
# ax = fig.add_subplot(111)

# ax.contourf(x, y, z)
# plt.show()
import numpy as np
import matplotlib.pyplot as plt

# x = np.linspace(-5, 5, 100)
# y = np.linspace(-5, 5, 100)
# X, Y = np.meshgrid(x, y)
# Z = X * Y / (X ** 2 + Y ** 2)

# fig = plt.figure()
# ax = fig.add_subplot(111, projection='3d')
# ax.plot_surface(X, Y, Z)

# plt.show()
print(-1%90)